Kubeflow
- Category
- AI and LLMs
- Docs outline
- 10 sections
Official docs outline
kubeflow.org- Kubeflow architecture and overview
How Kubeflow's components fit together on Kubernetes.
- Kubeflow Pipelines
Defining and running ML workflows with components and the KFP SDK.
- Pipelines concepts
Pipelines, components, runs, experiments, and artifacts.
- Kubeflow Trainer
Distributed training jobs for PyTorch, JAX, and other frameworks.
- Katib hyperparameter tuning
Automated hyperparameter tuning and neural architecture search.
- Kubeflow Notebooks
Managed Jupyter and IDE servers in the cluster.
- Spark Operator
Running Spark applications on Kubernetes.
- Model Registry
Tracking registered model versions and metadata.
- Central dashboard and multi-user isolation
Profiles, namespaces, and access control.
- Installation and distributions
Manifests and packaged distributions for deploying Kubeflow.
Each section links to the official page. Titles and summaries by Extra Credit; the docs belong to their authors.
